3D LiDAR Object Detection & Tracking using Euclidean Clustering, RANSAC, & Hungarian Algorithm
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Updated
Mar 20, 2024 - C++
3D LiDAR Object Detection & Tracking using Euclidean Clustering, RANSAC, & Hungarian Algorithm
Process LIDAR point cloud data for object detection. Implements RANSAC and Euclidean clustering with KD-Tree
Point Cloud 3D Visual Perception Simulation that runs on real LiDAR data
Obstacle Detection using LiDAR Point Cloud, RANSAC, and Euclidean Clustering.
Real-time 3D obstacle detection using LiDAR point clouds with custom RANSAC, KD-Tree, and Euclidean clustering algorithms for autonomous driving applications.
Projects Implemented for the Udacity Sensor Fusion Engineer Nanodegree Program
The main goal of this project is to detect objects in a point cloud stream.
Lidar Obstacle Detection using RANSAC and Euclidean Clustering
Sensor Fusion Lidar Obstacle Detection
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